Premium: An R package for profile regression mixture models using dirichlet processes

PReMiuM is a recently developed R package for Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, nonparametrically linking a response vector to covariate data through cluster membership (Molitor, Papathomas, Jerrett, and Richardson 2010). The package allows binary, categorical, count and continuous response, as well as continuous and discrete covariates. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection

A life history analysis of a male athlete with an eating disorder

An exploratory investigation, employing the life history method, was conducted with a male athlete with an eating disorder. The focus of the life history is Mike (pseudonym), an individual with a strong athletic identity, who developed bulimia amidst aspirations to be an elite sports performer. Interviews were structured around the life course, beginning with early childhood memories and ultimately reaching the present day. His narrative suggests the achievement threats and weight-based performance pressures associated with competitive sport played a role in precipitating the onset of bulimia nervosa. When such performance pressures were removed the eating disorder remained and evolved, suggesting that disordered eating in sport can have deeper roots as opposed to being primarily situational. Recovery coincided with the cessation of sport participation and the opening up of a foreclosed identity

Eating Disorders in Sport : a call for methodological diversity

From the emergence of isolated studies in the early 1980s to the concentrated and burgeoning research base of the present day, scholars within sport psychology have been motivated to address the problem of eating disorders in sport. Heavily influenced by the medical model of scientific inquiry, the extant literature offers important insights into prevalence and aetiology. Despite this progress, there is much that is poorly understood about athlete eating disorders and existing approaches are vulnerable to considerable critique. This paper highlights some of the fundamental problems with the medical model and argues that its current dominance has created an overly narrow knowledge base. It is proposed that an increase in qualitative, interpretive accounts, that prioritize the subjectivity of experience over the serialization of symptoms, is necessary if we are to achieve a balanced and more complete understanding of eating disorders in sport

On the correspondence of deviances and maximum-likelihood and interval estimates from log-linear to logistic regression modelling

Funding: The first author would like to acknowledge the support of the School of Mathematics and Statistics, as well as CREEM, at the University of St Andrews, and the University of St Andrews St Leonard’s 7th Century Scholarship.Consider a set of categorical variables P where at least one, denoted by Y, is binary. The log-linear model that describes the contingency table counts implies a logistic regression model, with outcome Y. Extending results from Christensen (1997, Log-linear models and logistic regression, 2nd edn. New York, NY, Springer), we prove that the maximum-likelihood estimates (MLE) of the logistic regression parameters equals the MLE for the corresponding log-linear model parameters, also considering the case where contingency table factors are not present in the corresponding logistic regression and some of the contingency table cells are collapsed together. We prove that, asymptotically, standard errors are also equal. These results demonstrate the extent to which inferences from the log-linear framework translate to inferences within the logistic regression framework, on the magnitude of main effects and interactions. Finally, we prove that the deviance of the log-linear model is equal to the deviance of the corresponding logistic regression, provided that no cell observations are collapsed together when one or more factors in P∖{Y} become obsolete. We illustrate the derived results with the analysis of a real dataset.Publisher PDFPeer reviewe

Implicit Attentional Selection of Bound Visual Features

SummaryTraditionally, research on visual attention has been focused on the processes involved in conscious, explicit selection of task-relevant sensory input. Recently, however, it has been shown that attending to a specific feature of an object automatically increases neural sensitivity to this feature throughout the visual field. Here we show that directing attention to a specific color of an object results in attentional modulation of the processing of task-irrelevant and not consciously perceived motion signals that are spatiotemporally associated with this color throughout the visual field. Such implicit cross-feature spreading of attention takes place according to the veridical physical associations between the color and motion signals, even under special circumstances when they are perceptually misbound. These results imply that the units of implicit attentional selection are spatiotemporally colocalized feature clusters that are automatically bound throughout the visual field

Bela Julesz in Depth

A brief tribute to Bela Julesz (1928−2003) is made in words and images. In addition to a conventional stereophotographic portrait, his major contributions to vision research are commemorated by two ‘perceptual portraits’, which try to capture the spirit of his main accomplishments in stereopsis and the perception of texture

Adrenocortical neoplasia: evolving concepts in tumorigenesis with an emphasis on adrenal cortical carcinoma variants

Adrenocortical carcinoma (ACC) is a rare, heterogeneous malignancy with a poor prognosis. According to WHO classification 2004, ACC variants include oncocytic ACCs, myxoid ACCs and ACCs with sarcomatous areas. Herein, we provide a comprehensive review of these rare subtypes of adrenocortical malignancy and emphasize their clinicopathological features with the aim of elucidating aspects of diagnostic categorization, differential diagnostics and biological behavior. The issue of current terminology, applied to biphasic tumors with pleomorphic, sarcomatous or sarcomatoid elements arising in adrenal cortex, is also discussed. We additionally present emerging evidence concerning the adrenal cortical tumorigenesis and the putative adenoma–carcinoma sequence as well